标题：Monitoring Arsenic Contamination in Agricultural Soils with Reflectance Spectroscopy of Rice Plants作者：Shi, Tiezhu; Liu, Huizeng; Wang, Junjie; Chen, Yiyun; Fei, Teng; Wu,Guofeng
来源出版物：ENVIRONMENTAL SCIENCE & TECHNOLOGY 卷：48 期：11 页：6264-6272 DOI：10.1021/es405361n 出版年：JUN 3 2014
摘要：The objective of this study was to explore the feasibility and to investigate the mechanism for rapidly monitoring arsenic (As) contamination in agricultural soils with the reflectance spectra of rice plants. Several data pretreatment methods were applied to improve the prediction accuracy. The prediction of soil As contents was achieved by partial least-squares regression (PLSR) using laboratory and field spectra of rice plants, as well as linear regression employing normalized difference spectral index (NDSI) calculated from fild spectra. For laboratory spectra, the optimal PLSR model for predicting soil As contents was achieved using Savitzky-Golay smoothing (SG), first derivative and mean center (MC) (root-mean-square error of prediction (RMSEP) = 14.7 mg kg(-1); r = 0.64; residual predictive deviation (RPD) = 1.31). For field spectra, the optimal PLSR model was also achieved using SG, first derivative and MC (RMSEP = 13.7 mg kg(-1); r = 0.71; RPD = 1.43). In addition, the NDSI with 812 and 782 nm obtained a prediction accuracy with r = 0.68, RMSEP = 13.7 mg kg(-1), and RPD = 1.36. These results indicated that it was feasible to monitor the As contamination in agricultural soils using the reflectance spectra of rice plants. The prediction mechanism might be the relationship between the As contents in soils and the chlorophyll-a/-b contents and cell structure in leaves or canopies of rice plants.
入藏号：WOS:000336952000026
文献类型：Article
语种：English
扩展关键词：HEAVY-METAL POLLUTION; ORYZA-SATIVA L.; FIELD SPECTROSCOPY; RIVER FLOODPLAINS; MINING AREA; GROWTH; PHOTOSYNTHESIS; ACCUMULATION; NITROGEN; STRESS
通讯作者地址：Wu, Guofeng; Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Natl Adm Surveying Mapping & Geoinformat, Shenzhen 518060, Peoples R China.
电子邮件地址：
地址：
[Shi, Tiezhu; Liu, Huizeng; Wang, Junjie; Chen, Yiyun; Fei, Teng; Wu, Guofeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
[Shi, Tiezhu; Liu, Huizeng; Wang, Junjie; Chen, Yiyun; Fei, Teng; Wu, Guofeng] Wuhan Univ, Key Lab Geog Informat Syst, Minist Educ, Wuhan 430079, Peoples R China.
[Wu, Guofeng] Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Natl Adm Surveying Mapping & Geoinformat, Shenzhen 518060, Peoples R China.
[Wu, Guofeng] Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China.
[Wu, Guofeng] Shenzhen Univ, Coll Life Sci, Shenzhen 518060, Peoples R China.
研究方向：Engineering; Environmental Sciences & Ecology
ISSN：0013-936X
